The Drought Monitoring, Precaution and Loss Estimating in China

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1 The Drought Monitoring, Precaution and Loss Estimating in China Dr. CHEN Huailiang (Henan Institute of Meteorological Sciences,China)

2 OUTLINE Forewords 1. Drought monitoring 2. Drought warning 3 Assessment of drought effects 4. Advice on future research of drought

3 Forewords Drought is the most common natural disaster. As estimated, globally economic loss due to drought reaches about 60~80 billion US$ every year, and far more than other meteorological disasters. China is a country with a vast and complex geographic environment and all kinds of natural disaster. As estimation, 70% of natural disasters belong to meteorological disaster, and drought disaster accounts for about 50% of meteorological disasters.

4 In recent years, drought is becoming more severe and affects crop production in China. In China, crop loss due to drought reaches about 25~30 million ton every year at least, and accounts for about 60% of all loss due to natural disasters.

5 The statistical results showed that heavy drought recur frequency was very high in Huanghe -huaihe-haihe area, it is 26.9% in yellow river basin, 30.3% in Haihe river basin and 33.6% in Huaihe river basin respectively. The drought area in Huanghe-huaihehaihe account for 50% in China.

6 Subsequently, the introduction is given about the drought monitoring, warning and loss estimating to winter wheat in China.

7 1. Drought monitoring Drought s classification and definition Traditional observing method of soil moisture Automatic observing of soil water The satellite remote sensing in soil moisture Meteorological drought index-the application of Palmer Index

8 1.1 Drought s classification and definition There are 5 types classification and definition in the view from different branches. (1) Meteorological Drought, defined by precipitation deficiencies, applied in weather, climate operation.

9 (2) Agricultural Drought, defined by soil moisture deficiencies and crop lacks in water, applied in agrometeorological operation.

10 (3)Hydrological Drought, defined by declining surface and groundwater supplies.

11 (4) Socioeconomic Drought, defined as drought that impacts supply and demand of some economic commodity.

12 (5) Hydrological Drought & Land Use, defined as a meteorological drought in one area that has hydrological impacts in another area by the Missouri Drought Response Plan of USA.

13 1.2 Traditional observing method of soil water The main method for observing soil water in all levels of meteorological station is soil auger. Advantages: high precision Disadvantages: Poor representation, Time-consuming and laborious.

14 1.3 Automatic observing of soil water (1) Neutron probe Advantages: Rapid and laborsaving, no destruction of soil Disadvantages: calibration equation is complex, poor representation and expensive cost.

15 (2) Time Domain Reflector (TDR) Advantages: High precision, Non-radioactive, suitability for long term and Continuous observation Disadvantages: Expensive price, complicated installation, Heavy workload and difficult maintenance

16 (3) Frequency Domain Reflector (FDR) Advantages: high precision, rapid and accurate, continuous measurement, no destruction of soil, automatic observation on variations of soil water, economic and durable, Nonradioactive Disadvantages: observing precision affected by soil properties such as salinity, clay and bulk density etc.

17 The automatic FDR soil moisture monitor:gstar-1 Henan Institute of Meteorological Sciences developed a new kind of automatic FDR soil water monitor- GSTAR-1. This instrument is easy to install and maintain, and has a high degree of automation.

18 Gstar-1 type FDR automatic soil water monitor has reached similar foreign products levels (such as Australia, SMART, etc.), and its patent has been approved through the National Patent Office. Patent No

19 Agrilink Holdings, total number of capacitance sensors sold w orldw ide from 1998 through 2007 (Dr. David Sloane, personal communication) TOTAL Automatic TDR or FDR soil moisture monitoring instruments have been widely used in the world. However, they are rarely used in agrometeorological daily operation in China. Percentage of total sensors sold worldwide (%) Percentage of total sensors sold worlwide by continents, Agrilink Holdings, Thebarton, Australia (Dr. David Sloane - Personal Communication) Africa Asia Australia & Oceania Europe North & Central America South America

20 1.4 The satellite remote sensing in soil moisture The methods based on thermal infrared spectrum are normalized difference vegetation Index(NDVI), vegetation condition index(vci), average vegetation index(avi), perpendicular drought index(pdi), modified perpendicular drought index(mpdi), temperature condition index(tci), normalized difference temperature index(ndti), apparent thermal inertia vegetation drought index(avdi), vegetationtemperature condition index(vtci), vegetationtemperature trapezoid index(vitt), temperaturevegetation drought index(tvdi), crop water stress index(cwsi) etc.

21 Airborne remote sensing and microwave remote sensing in drought Airborne remote sensing is maneuvering and flexible, the plane (and unmanned piloting plane) is main platform. For the advantage of its high resolution, short time cycle investigation, not limited to ground status and data easier get etc. It is suit for drought monitoring in small scale and details investigate.

22 The flight altitude, sustainable flight ability, attitude control, all weather operation ability and dynamic monitoring in large scale were its main shortcomings.

23 The microwave remote sensing has a lot of advantages compare with satellite remote sensing. It is the most promising method to solve the problem of drought monitoring. (1) Microwave ratio is high and has a high distinguish power to different objects. (2) With a higher penetrate power to cloud, easier get upper air images. (3) The powerful penetrate strength make the information underground easy to get. (4) Also get the soil and vegetation information in geometry cubic and medium characters.

24 1.5 Construction and Validation of a New Model for Crop Soil Moisture Index based on EOS/MODIS data The ratio of the root to canopy has been changing along with the crops growth. In the early stage, the crops roots most located in the depth of 0~20cm. after some period of growth, the most roots located in the depth of 20-50cm. The more lack of water in soil, the crop s root depth deeper, vice versa. The soil water condition in the depth of 20-50cm could be reflected by the vegetation index-ndvi, so the combination of Band1 and Band2, the NDVI, has been figure out and could reflect the water condition in the depth of 20~50cm.

25 The Surface Water Content Index (SWCI), which based on water absorption and soil reflection spectrum that Band6 and Band7 fully utilize, can better reflect the water content in soil surface(0~20cm), while it is not satisfied when used in the deeper soil moisture monitoring.

26 Compare with two group data and we found that the value of NDVI is higher than SWCI Date Index Calculating results 03/07/ 2007 NDVI SWCI /24/ 2008 NDVI SWCI

27 With the character analysis of NDVI and SWCI, we found that neither NDVI nor SWCI could reflect the water condition in the depth of 0~50cm separately. So, we figure out a new index which is the combination of Band1, Band2, Band6 and Band7 Crop Soil Moisture Index (CSMI).

28 For comparing with other Index, the method of Normalization has been taken in here CSMI 2 NDVI NDVI To EOS/MODIS data, Substituted B2 B1 NDVI B B 1 and SWCI SWCI SWCI in equation of CSMI, then simplified as B B 6 6 B B 7 7 CSMI B B 2 2 B B 7 6 B B 1 1 B B 6 7

29 Not only the CSMI considers the spectrum of soil surface water content, but also the spectrum of NDVI which reflect the deeper soil moisture, so the index of CSMI can effectively minimize the vegetation cover which do affect on the accuracy of soil moisture monitoring.

30 Analysis on the result of effectiveness validation The regression and effectiveness validation of CSMI NDVI and SWCI model Date Indices Regression Model Samples R 2 Correlation coefficient F-Value Prob>F NDVI Y = X SWCI Y = X CSMI Y = 56.96X NDVI Y = X SWCI Y = X CSMI Y =87.74X NDVI Y = -7.48X SWCI Y = X CSMI Y = 72.75X NDVI Y = X SWCI Y = X CSMI Y = 90.85X NDVI Y = X SWCI Y = X CSMI Y = 68.87X

31 Measured relative moisture Simulated relative moisture

32 The distribution comparison of CSMI and Actual Relative Soil Moisture The sketch map of CSMI on May, 8 th, 2007 The sketch map of RSM in spots on May, 8 th, 2007

33 Model of CSMI interpret the soil moisture index directly from which it fully consider the surface water content (SWCI) and NDVI which reflect the soil water condition in depth. The combination of Band1 and Band2 has been best reflecting the condition of vegetation status. The combination of Band6 and Band7 could interpret the surface water content directly while it could minimize the atmosphere interference. The integrating of 4 bands (Band1, Band2, Band6 and Band7) is more useful when it is used in the depth of 0~50cm drought monitoring.

34 1.6 The application of Palmer Drought Index in China Early in 1970s, Palmer Drought Index was introduced to China. With the global warming and climate changing, the application of PDI used not only in Meteorological Branch, but also in Agriculture, Hydrology etc. branches.

35 In 1985 year, Mr. An Shuiqing et al. modified the PDI model and developed the meteorological drought model suit for China with the utilization of weather data in North China. Model validation shows that it is suit for the area of Longitude>100 O E in China, and prove its application values in drought information, drought analysis and drought affection assessment etc. Now, Palmer Drought Index has become a main monitoring method in climate/agrometeorologcal operation.

36 2. Drought precation 2.1 Based on actual soil moisture data of weather station Forecasting soil moisture is the base of drought warning which based on soil moisture data of discrete weather stations, while soil water balance equation is the foundation to forecast soil moisture W T+1 W T P + G ET in which W T+1 soil moisture at the end of duration (mm) W T soil moisture at the beginning of duration (mm) P effective precipitation in duration (mm) G groundwater recharge in duration (mm) ET crop water consumption in duration (mm)

37 Using the actual soil moisture data, historical weather data and medium and long term weather forecasting results, the soil moisture forecasting and drought precaution system was established and improved. Through a series of trainings in meeting and onsite forms, we extend the system to some weather stations and supply drought warning services. Now, we have extended this system in Henan, Shandong, Jiangsu and Anhui Province.

38 The Flow Chart of Henan soil moisture forecasting and drought precaution Start Add real-time data Main Moduler Base parameters Actual data Weather forecast Crop stages History data rain Soil moisture Variable curve Data sheet Maize stges Wheat stages rain Temp. rainfall Soil moisture soil \ Hydrology Lat./Lon./Altitute calculating Humidity assessment Relative humidity Intending humidity Moisture under ground Intending rain Intending stages Multistation calc. Data sheet Soil moisture map End

39 Operational System interface

40 Operational System interface

41 Operational System interface

42 Operational System interface

43 Operational System interface

44 Operational System interface

45 Operational System interface

46 Operational System interface

47 2.2 Prediction of soil drought and irrigation based on grids In recent years, we are Improving the soil moisture forecasting and drought prediction system based on grids and apply it in operations. Based on remote sensing soil moisture monitoring model, regional climate model (RegCM3) and agro-meteorological model (Penman- Monteith equation) we established the grid soil moisture and drought prediction system and applied it in operations. By the system, regularly or irregularly precaution reports on soil moisture and drought forecast can be published to supervise the defense of agricultural drought. The accuracy of grids soil moisture forecasting of ten-days is above 85%.

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54 3 Assessment of drought effects 3.1 Assessment technologies Research on crop drought index By researches, Climate Drought Degree Index (CDDI) based on negative precipitation anomaly during whole season and jointing stage of winter wheat was established. After analyzing field experiment data, crop drought index was established by using the rate of water shortage during whole season, jointing and grain filling stage of winter wheat.

55 4.1.2 Risk analysis and assessment By considering the effects of climate, crop and agricultural production and analyzing on yield data, several methods were set up to evaluate the comprehensive drought risk in winter wheat production, and the methods including climate drought risk index, crop drought risk index and risk assessment method on drought loss and evaluation method on comprehensive risk. The winter wheat area in Henan province was divided into three regions: high risk region, medium risk region and low risk region.

56 4.1.3 Disaster loss estimating Considering the costs of reduce disaster, the estimating model of economic drought loss of winter wheat is established: in which, e is the economic loss of unit area (RMB/ha); f 1 is yield loss of unit area, and varies with meteorological yield (y w ) and wheat price (p); is irrigation coefficient, refer to the rate between actual irrigated area and sowing area; f 2 is the total irrigation input of unit area during growing season, and it is determined by irrigation times (n), water cost of each irrigation (w), electricity cost of unit irrigation (e), labor cost of unit irritation (m); R is the negative precipitation anomaly during growing season of winter wheat.

57 3.2 Operational and serving system of winter wheat drought assessment By integrating many indexes and models, the operation and serving system of winter wheat drought assessment was set up.

58 3.2.1 System structure The system was consist of data-base, knowledge-base (models and indexes), reasoning-base (calculating tools etc. It was programmed by using Access2003 and VBA language and run under Ms Office XP or Ms Office 2003 environment. Access2002 and Access2003 was necessary component.

59 3.2.2 System functions The system has the following functions: queries on basic parameters, drought risk index and zoning data, risk analysis, risk assessment, disaster loss assessment et al. It also supply the functions of risk analysis before winter wheat sowing, disaster loss assessment after harvest and assessment during growing season.

60 4. Advice on future research of drought 4.1 Drought monitoring (1) Remote sensing is one of the most promising methods for drought monitoring. However, the mechanism model of drought remote sensing monitoring is still lacking, most current models are semistatistical and semi-mechanism. Parameters in these models are varied with seasons, crops and areas and are less universal. In the future, more efforts should be devote to develop the mechanism models on drought. (2) The reality of drought remote sensing monitoring should be put more emphasis in future because of its difficulty in validation. (3) Single method is difficult to solve problems in drought remote sensing monitoring. Integrated technologies of drought remote sensing monitoring are urgent to be developed.

61 (4) In usual operations, soil moisture data are obtained mainly by manual, the degree of automation is still low and poor timeliness. Therefore, the situation is difficult to meet the requirement of agrometeorological operations, needs the automatic soil moisture monitoring implements with high performance and low prices. (5)Meteorological drought and agricultural drought are different. And agro-meteorology put more focus on the latter. However, agricultural drought concerns many factors, and has much difficulty in operation. Therefore, more attention and support from WMO are required at observing index, methods and models.

62 4.2 Drought warning (1) Accuracy and timeliness of current service products in drought warning operations need to be increased due to the effects of accuracy and timeliness in weather forecast and short-term climate prediction. (2) Supplying more accurate products in soil moisture and drought warning using remote sensing, digital weather forecast (NWP) and agro-meteorological models is one of the major developing directions. And this need more attentions.

63 4.3 Drought assessment 1 Requiring relevant researches to develop systematic assessment indexes. 2 Quantitative and dynamic assessment models are lacking. Currently, most assessment models only can do the static evaluations after disaster events, and can not meet the requirement of modern agrometeorological operations. 3 The timeliness of assessment is not enough. The lack of the necessary emergency equipment for field survey seriously restrict the effects of assessment and on-site response to emergence and service capabilities.

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